pushing files to the repo from the example!
Browse files- README.md +131 -0
- config.json +63 -0
- skops-nxorv9li.pkl +3 -0
README.md
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@@ -0,0 +1,131 @@
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---
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library_name: sklearn
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tags:
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- sklearn
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- skops
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- tabular-regression
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widget:
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structuredData:
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Hour:
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- 0
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- 1
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- 2
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Lag_1:
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- 4.215
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- 1.741
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- 1.38
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Lag_2:
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- 3.939
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- 4.215
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- 1.741
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Lag_3:
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- 4.222
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- 3.939
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- 4.215
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Lag_4:
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- 4.568
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- 4.222
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- 3.939
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Temperature:
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- 20.45
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- 19.5
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- 18.75
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Weekday:
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- 4
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- 4
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- 4
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Weekofyear:
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- 1
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- 1
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- 1
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---
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# Model description
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[More Information Needed]
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## Intended uses & limitations
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[More Information Needed]
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## Training Procedure
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### Hyperparameters
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The model is trained with below hyperparameters.
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<details>
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<summary> Click to expand </summary>
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| Hyperparameter | Value |
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|--------------------------|---------------|
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| bootstrap | True |
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| ccp_alpha | 0.0 |
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| criterion | squared_error |
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| max_depth | 10 |
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| max_features | 1.0 |
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| max_leaf_nodes | |
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| max_samples | |
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| min_impurity_decrease | 0.0 |
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| min_samples_leaf | 1 |
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| min_samples_split | 2 |
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| min_weight_fraction_leaf | 0.0 |
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| n_estimators | 50 |
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| n_jobs | |
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| oob_score | False |
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| random_state | 59 |
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| verbose | 0 |
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| warm_start | False |
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</details>
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### Model Plot
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The model plot is below.
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<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-2" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>RandomForestRegressor(max_depth=10, n_estimators=50, random_state=59)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" checked><label for="sk-estimator-id-2" class="sk-toggleable__label sk-toggleable__label-arrow">RandomForestRegressor</label><div class="sk-toggleable__content"><pre>RandomForestRegressor(max_depth=10, n_estimators=50, random_state=59)</pre></div></div></div></div></div>
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## Evaluation Results
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You can find the details about evaluation process and the evaluation results.
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| Metric | Value |
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|----------|---------|
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# How to Get Started with the Model
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Use the code below to get started with the model.
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<details>
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<summary> Click to expand </summary>
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```python
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[More Information Needed]
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```
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</details>
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# Model Card Authors
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This model card is written by following authors:
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[More Information Needed]
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# Model Card Contact
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You can contact the model card authors through following channels:
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[More Information Needed]
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# Citation
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Below you can find information related to citation.
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**BibTeX:**
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```
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[More Information Needed]
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```
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config.json
ADDED
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{
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"sklearn": {
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"columns": [
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"Weekofyear",
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"Weekday",
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"Hour",
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"Temperature",
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"Lag_1",
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"Lag_2",
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"Lag_3",
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"Lag_4"
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],
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"environment": [
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"scikit-learn=1.1.1"
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],
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"example_input": {
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"Hour": [
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0,
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1,
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2
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],
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"Lag_1": [
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4.215,
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1.741,
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1.38
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],
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"Lag_2": [
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3.939,
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4.215,
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1.741
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],
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"Lag_3": [
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4.222,
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3.939,
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4.215
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],
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"Lag_4": [
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4.568,
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4.222,
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3.939
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],
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"Temperature": [
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20.45,
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19.5,
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18.75
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],
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"Weekday": [
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4,
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4,
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4
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],
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"Weekofyear": [
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1,
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1,
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1
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]
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},
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"model": {
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"file": "skops-nxorv9li.pkl"
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},
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"task": "tabular-regression"
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}
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}
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skops-nxorv9li.pkl
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:347ed2cc6405af494014208130df05833de901f36d6f8af290033cd2cb044e2d
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size 643
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